How I Decide Whether to Split a Team
Most advice on splitting teams answers 'is this team too big?' That's the wrong question when you're splitting into a strategy.
Actionable guides and mental models for engineering leaders who believe management can be people-first, humane, and a real enabler.
Most advice on splitting teams answers 'is this team too big?' That's the wrong question when you're splitting into a strategy.
Most engineering orgs run a hard job attached to an easy idea. How to tell the difference, and what to do about it.
Why do organizations defend failing decisions? Learn how to record assumptions, set review triggers, and change course without turning to blame.
Learn how managers can transfer context, judgment, and decision-making ability so their teams operate independently without losing direction.
Goodhart's law is only half the story. The real risk in engineering metrics isn't gaming, it's losing the palate to tell good work from the look of it.
Pain is a side effect, not the active ingredient. Proximity to consequences is what teaches.
Typing code was doing load-bearing QA work nobody invoiced for. Agents removed the slowness, and now the work has to live somewhere on purpose.
A fast engineering team is not automatically a productive one. The real test is whether the work changes anything that matters.
Career frameworks describe outcomes, not behaviors; interviewers collect impressions, not evidence. Here's how to fix both.
AI didn't break pull requests; it exposed the review queues, slow integration, and weak collaboration habits engineering teams already had.
Burnout has a different shape at every rung of the engineering ladder, and promotion doesn't cure it: it just trades one variant for another.
AI is cutting junior hiring. But the engineers that won't exist in 10 years are being decided right now. Here's what I think actually happens next.
Your team is not a school. You are not a teacher. The studio model is what actually grows engineers, and most of us are running classrooms.
Most 360 feedback fails not because leaders don't try to change, but because changed behavior doesn't automatically update other people's mental models.
AI doesn't care about quality. It accelerates whatever direction your team was already heading. Here's what engineering leaders need to change.